Physics of the Future: How Science Will Shape Human Destiny and Our Daily Lives by the Year 2100

in the cracks, all within a matter of seconds.
    AI researcher Thomas Dean of Brown University has admitted that the lumbering robots he is building are “ just at the stage where they’re robust enough to walk down the hall without leaving huge gouges in the plaster.” As we shall later see, at present our most powerful computers can barely simulate the neurons of a mouse, and then only for a few seconds. It will take many decades of hard work before robots become as smart as a mouse, rabbit, dog or cat, and then a monkey.
    HISTORY OF AI
    Critics sometimes point out a pattern, that every thirty years, AI practitioners claim that superintelligent robots are just around the corner. Then, when there is a reality check, a backlash sets in.
    In the 1950s, when electronic computers were first introduced after World War II, scientists dazzled the public with the notion of machines that could perform miraculous feats: picking up blocks, playing checkers, and even solving algebra problems. It seemed as if truly intelligent machines were just around the corner. The public was amazed; and soon there were magazine articles breathlessly predicting the time when a robot would be in everyone’s kitchen, cooking dinner, or cleaning the house. In 1965, AI pioneer Herbert Simon declared, “ Machines will be capable, within twenty years, of doing any work a man can do.” But then the reality set in. Chess-playing machines could not win against a human expert, and could play only chess, nothing more. These early robots were like a one-trick pony, performing just one simple task.
    In fact, in the 1950s, real breakthroughs were made in AI, but because the progress was vastly overstated and overhyped, a backlash set in. In 1974, under a chorus of rising criticism, the U.S. and British governments cut off funding. The first AI winter set in.
    Today, AI researcher Paul Abrahams shakes his head when he looks back at those heady times in the 1950s when he was a graduate student at MIT and anything seemed possible. He recalled, “ It’s as though a group of people had proposed to build a tower to the moon. Each year they point with pride at how much higher the tower is than it was the previous year. The only trouble is that the moon isn’t getting much closer.”
    In the 1980s, enthusiasm for AI peaked once again. This time the Pentagon poured millions of dollars into projects like the smart truck, which was supposed to travel behind enemy lines, do reconnaissance, rescue U.S. troops, and return to headquarters, all by itself. The Japanese government even put its full weight behind the ambitious Fifth Generation Computer Systems Project, sponsored by the powerful Japanese Ministry of International Trade and Industry. The Fifth Generation Project’s goal was, among others, to have a computer system that could speak conversational language, have full reasoning ability, and even anticipate what we want, all by the 1990s.
    Unfortunately, the only thing that the smart truck did was get lost. And the Fifth Generation Project, after much fanfare, was quietly dropped without explanation. Once again, the rhetoric far outpaced the reality. In fact, there were real gains made in AI in the 1980s, but because progress was again overhyped, a second backlash set in, creating the second AI winter, in which funding again dried up and disillusioned people left the field in droves. It became painfully clear that something was missing.
    In 1992 AI researchers had mixed feelings holding a special celebration in honor of the movie
2001,
in which a computer called HAL 9000 runs amok and slaughters the crew of a spaceship. The movie, filmed in 1968, predicted that by 1992 there would be robots that could freely converse with any human on almost any topic and also command a spaceship. Unfortunately, it was painfully clear that the most advanced robots had a hard time keeping up with the intelligence of a bug.
    In 1997 IBM’s Deep Blue accomplished a historic breakthrough by decisively beating the world chess champion Gary Kasparov. Deep Blue was an engineering marvel, computing 11 billion operations per second. However, instead of opening the floodgates of artificial intelligence research and ushering in a new age, it did precisely the opposite. It highlighted only the primitiveness of AI research. Upon reflection, it was obvious to many that Deep Blue could not think. It was superb at chess but would score 0 on an IQ exam. After this victory, it was the